Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Large-Scale Concept Ontology for Multimedia
IEEE MultiMedia
The challenge problem for automated detection of 101 semantic concepts in multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Cross-domain video concept detection using adaptive svms
Proceedings of the 15th international conference on Multimedia
Spectral regression: a unified subspace learning framework for content-based image retrieval
Proceedings of the 15th international conference on Multimedia
Optimizing multi-graph learning: towards a unified video annotation scheme
Proceedings of the 15th international conference on Multimedia
Discriminant subspace analysis: an adaptive approach for image classification
IEEE Transactions on Multimedia
A kernel density based approach for large scale image retrieval
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Double fusion for multimedia event detection
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
TaylorBoost: First and second-order boosting algorithms with explicit margin control
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
A Multimedia Retrieval Framework Based on Semi-Supervised Ranking and Relevance Feedback
IEEE Transactions on Pattern Analysis and Machine Intelligence
Can High-Level Concepts Fill the Semantic Gap in Video Retrieval? A Case Study With Broadcast News
IEEE Transactions on Multimedia
Association and Temporal Rule Mining for Post-Filtering of Semantic Concept Detection in Video
IEEE Transactions on Multimedia
Video Semantic Event/Concept Detection Using a Subspace-Based Multimedia Data Mining Framework
IEEE Transactions on Multimedia
IEEE Transactions on Multimedia
IEEE Transactions on Multimedia
Video Annotation Through Search and Graph Reinforcement Mining
IEEE Transactions on Multimedia
A Survey on Visual Content-Based Video Indexing and Retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Video annotation and multimedia classification play important roles in many applications such as video indexing and retrieval. To improve video annotation and event detection, researchers have proposed using intermediate concept classifiers with concept lexica to help understand the videos. Yet it is difficult to judge how many and what concepts would be sufficient for the particular video analysis task. Additionally, obtaining robust semantic concept classifiers requires a large number of positive training examples, which in turn has high human annotation cost. In this paper, we propose an approach that is able to automatically learn an intermediate representation from video features together with a classifier. The joint optimization of the two components makes them mutually beneficial and reciprocal. Effectively, the intermediate representation and the classifier are tightly correlated. The classifier dependent intermediate representation not only accurately reflects the task semantics but is also more suitable for the specific classifier. Thus we have created a discriminative semantic analysis framework based on a tightly-coupled intermediate representation. Several experiments on video annotation and multimedia event detection using real-world videos demonstrate the effectiveness of the proposed approach.